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Eigenvector centrality

In graph theory, eigenvector centrality (also called eigencentrality) is a measure of the influence of a node in a network. It assigns relative… Expand
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Papers overview

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2019
2019
Eigenvector centrality is a standard network analysis tool for determining the importance of (or ranking of) entities in a… Expand
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2018
2018
Eigenvector-based centrality measures are among the most popular centrality measures in network science. The underlying idea is… Expand
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2016
2016
In an era where accumulating data is easy and storing it inexpensive, feature selection plays a central role in helping to reduce… Expand
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Highly Cited
2015
Highly Cited
2015
Recently, there has been a growing interest in the use of brain activity for biometric systems. However, so far these studies… Expand
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Highly Cited
2015
Highly Cited
2015
Radio-frequency (RF) enabled wireless energy transfer (WET), as a promising solution to provide cost-effective and reliable power… Expand
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Highly Cited
2008
Highly Cited
2008
Interactive segmentation is often performed on images that have been stored on disk (e.g., a medical image server) for some time… Expand
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Highly Cited
2007
Highly Cited
2007
Abstract Eigenvectors, and the related centrality measure Bonacich's c(β), have advantages over graph-theoretic measures like… Expand
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Highly Cited
2004
Highly Cited
2004
We introduce a stochastic graph-based method for computing relative importance of textual units for Natural Language Processing… Expand
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Highly Cited
2004
Highly Cited
2004
We introduce a stochastic graph-based method for computing relative importance of textual units for Natural Language Processing… Expand
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Highly Cited
1994
Highly Cited
1994
We study the topology of symmetric, second-order tensor fields. The goal is to represent their complex structure by a simple set… Expand
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